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Review
. 2025 Jun 10;13(6):1420.
doi: 10.3390/biomedicines13061420.

Computational Neuroscience's Influence on Autism Neuro-Transmission Research: Mapping Serotonin, Dopamine, GABA, and Glutamate

Victoria Bamicha  1 , Pantelis Pergantis  1   2 , Charalabos Skianis  2 , Athanasios Drigas  1
Affiliations
Review

Computational Neuroscience's Influence on Autism Neuro-Transmission Research: Mapping Serotonin, Dopamine, GABA, and Glutamate

Victoria Bamicha et al. Biomedicines. .

Abstract

Autism spectrum disorder is a complex and diverse neurobiological condition. Understanding the mechanisms and causes of the disorder requires an in-depth study and modeling of the immune, mitochondrial, and neurological systems. Computational neuroscience enhances psychiatric science by employing machine learning techniques on neural networks, combining data on brain activity with the pathophysiological and biological characteristics of psychiatric-neurobiological disorders. The research explores the integration of neurotransmitter activity into computational models and their potential roles in diagnosing and treating autism using computational methods. This research employs a narrative review that focuses on four neurotransmitter systems directly related to the manifestation of autism, specifically the following neurotransmitters: serotonin, dopamine, glutamate, and gamma-aminobutyric acid (GABA). This study reveals that computational neuroscience advances autism diagnosis and treatment by identifying genetic factors and improving the efficiency of diagnosis. Neurotransmitters play a crucial role in the function of brain cells, enhancing synaptic conduction and signal transmission. However, the interaction of chemical compounds with genetic factors and network alterations influences the pathophysiology of autism. This study integrates the investigation of computational approaches in four neurotransmitter systems associated with ASD. It improves our understanding of the disorder and provides insights that could stimulate further research, thereby contributing to the development of effective treatments.

Keywords: GABAergic system; autism spectrum disorder; computational modeling; computational neuroscience; computational psychiatry; dopaminergic system; glutamatergic system; machine learning; neurotransmitter function; serotonergic system.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Computational methods and artificial intelligence tools improve the effectiveness of computational science.
Figure 2
Figure 2
Sorting GABA, serotonin, glutamate, and dopamine based on their roles.
Figure 3
Figure 3
Neurotransmission is connected to the emergence of ASD symptoms.
Figure 4
Figure 4
Computational neuroscience interacts with other scientific disciplines.
See this image and copyright information in PMC

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